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motion and the viewing perspective of the observer (Nikolaidis et al, 2016). This project will develop continuous models of action legibility using these sources of information from data collected in a
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used to measure motion and deformation. It provides comprehensive full-field deformation data, essential for analysing complex materials, structures and model validation. The DIC community has developed
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the areas of fluid dynamics, turbulence and net-zero combustion. There is substantial scope for the student to direct the project with the main focus on (i) Generating an advanced Direct Numerical Simulation
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modeling & environmental risk assessment. Numerical simulation techniques for hydrogeological systems. Advanced uncertainty quantification for robust modeling. Scientific communication, including
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coalitions for delivering reliable, low-carbon energy services. Collaborating closely with UK Power Networks, SSE Energy Solutions, and the University of East London, you will develop robust economic Model
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experience in developing computational models and implementing models for computer simulations. Software development in C++ and/or Python is expected, and experience in model analysis and parameter
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., extracted from the collected data) and “predications” (generated by the C2 operational model). The tool will detect subtle discrepancies indicative of stealthy data manipulation with zero false alarms
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the development of a low fidelity pump model that accounts for unstable and multi-phase flow behaviour through high fidelity simulations. This will be used to develop an integrated fuel system model that will
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experience in developing computational models and implementing models for computer simulations. Software development in C++ and/or Python is expected, and experience in model analysis and parameter
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MRI, echocardiography, and CT. Another promising approach is the use of cardiac digital twins—mathematical models that simulate a patient’s heart to allow the design and in silico testing of novel